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Implementing visual assistant using YOLO and SSD for visually-impaired persons

Litoriya Ratnesh, Bandhu Kailash Chandra, Gupta Sanket, Rajawat IIshika, Jagwani Hany, Yadav Chirayu

Journal of Automation Mobile Robotics and Intelligent Systems

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2023

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Vol. 17, No. 4

79--87

EN

Artificial Intelligence has been touted as the next big thing that is capable of altering the current landscape of the technological domain. Through the use of Artificial Intelligence and Machine Learning, pioneering work has been undertaken in the area of Visual and Object Detection. In this paper, we undertake the analysis of a Visual Assistant Application for Guiding Visually-Impaired Individuals. With recent breakthroughs in computer vision and supervised learning models, the problem at hand has been reduced significantly to the point where new models are easier to build and implement than the already existing models. Different object detection models exist now that provide object tracking and detection with great accuracy. These techniques have been widely used in automating detection tasks in different areas. A few newly discovered detection approaches, such as the YOLO (You Only Look Once) and SSD (Single Shot Detector) approaches, have proved to be consistent and quite accurate at detecting objects in real-time. This paper attempts to utilize the combination of these state-of-the-art, real-time object detection techniques to develop a good base model. This paper also implements a ’Visual Assistant’ for visually impaired people. The results obtained are improved and superior compared to existing algorithms.

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SSD-based carton packaging quality defect detection system for the logistics supply chain

Song Bing, Wang Yan, Lou Li-Ping

Ecological Chemistry and Engineering. S

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2023

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Vol. 30, nr 1

117--123

EN

With the deepening of green and sustainable development and the rapid development of the social economy, the modern logistics industry has also developed to an unprecedented level. In the logistics supply chain, due to the high value of the items inside the arrival carton, appearance inspection must be carried out before warehousing. However, manual inspection is slow and ineffective, resulting in the waste of manpower and packaging carton resources, which is not conducive to sustainable development. To address the above problems, this paper designs a logistics supply chain carton packaging quality defect detection system based on improved Single Shot MultiBox Detector (SSD) in the context of green sustainable development. The Implicit Feature Pyramid Network (IFPN) is introduced into SSD to improve the feature extraction ability of the model; the multiscale attention mechanism is introduced to collect more feature information. The experiment shows that the mAP and FPS of the system on the self-built data set reach 0.9662 and 36 respectively, which can realise the detection of the appearance defects of logistics cartons and help promote green sustainable development.

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Tempo zużywania dysków SSD w maszynach wirtualnych

Wilczewski B., Lichy K.

Zeszyty Naukowe Wyższej Szkoły Informatyki

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2016

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Vol. 15, Nr 1

48--62

PL

Wirtualizacja to technologia powszechna obecnie w zastosowaniach profesjonalnych jak i prywatnych. To samo można powiedzieć o dyskach SSD konkurujących z "tradycyjnymi" dyskami magnetycznymi. W artykule opisano jak wpływają na siebie te dwie technologie. Dokładniej, odpowiedź na pytanie, czy stosowanie dysków SSD do wirtualizacji może prowadzić do szybszego ich zużycia.

EN

Virtualization is a technology born in the 20th century and commonly present in modern world: in professional as well as in private environment. The same can be said about Solid State Discs, which compete with ‘traditional’ magnetic discs. The purpose of the article is to check how these two technologies influence each other. More precisely, it helps to answer a question if using SSD for virtualization causes faster exploitation of the disc itself. Moreover, it gives an explanation, if using virtualization can lead to SSD’s operating extension.